Predictive analytics in recruitment is the process of using historical data to make predictions about future hiring activities and candidates. It includes collecting and analyzing data using statistics, machine learning, and modeling techniques to best predict what could happen under specific situations. For instance, the recruiter can use predictive analytics to determine if the candidate will be a good or bad hire. It does so by analyzing the candidate’s external inputs gathered by the ATS, from sources like their CV, cover letter, assessments and pre-screens, social media, etc.
To better understand the significance of predictive analytics, let’s take a look at some of the areas that it provides insight into:
The objective of data-driven recruitment is to leverage a large amount of data available with the recruiters to optimize and streamline the entire recruitment process and hire the best quality candidates. In addition to helping recruiters with accurate hiring, data analytics also make sure the recruitment process is more efficient and cost-effective.